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find-package

作者 fjh · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install find-package
功能描述
Help users locate their packages on delivery shelves by matching pickup codes to shelf photos. Trigger this skill when a user mentions finding packages, pick...
使用说明 (SKILL.md)

Find Package (找快递)

Help users find their packages on delivery station shelves. The user provides a pickup code and shelf photos, and you identify which package matches — marking it with a red bounding box and sending the annotated image back.

Workflow

Step 1: Get the pickup code (取件码)

Ask the user for their pickup code. Speak in Chinese — this is a Chinese-locale feature.

The user may respond with:

  • Plain text: e.g. "5-2-1234" or "五号架 二层 1234"
  • A screenshot: SMS notification or 菜鸟裹裹/丰巢/中通 app screenshot containing the code

Pickup code format: Typically X-Y-ZZZZ where X = shelf/section number, Y = row/layer, ZZZZ = code digits. Variations exist — some use Chinese characters, some just numbers. Extract whatever looks like a pickup reference code.

If the user sends an image, use your vision capabilities to read the pickup code from it. Look for patterns like:

  • 取件码:5-2-1234
  • 货架号:5 取件码:1234
  • 格口:5-2-1234

Confirm the extracted code with the user before proceeding: "我识别到的取件码是 5-2-1234,对吗?"

Step 2: Get shelf photos (货架照片)

Once you have the confirmed pickup code, ask the user to take photos of the package shelves. Tell them:

"请拍一下货架的照片发给我,可以一次发多张~"

The user may send:

  • A single photo of one shelf section
  • Multiple photos covering different shelf sections

Step 3: Recognize and match

For each shelf photo the user sends:

  1. Read the image with your vision capabilities — identify all visible package labels, tracking numbers, and pickup codes on the shelf
  2. Match the detected codes against the user's pickup code
  3. If a match is found:
    • Note the bounding box coordinates (in pixels) of the matching package label
    • Use the annotation script to draw a prominent red bounding box:
python3 {baseDir}/scripts/annotate.py \
  --input /path/to/shelf_photo.jpg \
  --output /tmp/find-package-result.jpg \
  --box "x1,y1,x2,y2" \
  --label "取件码: 5-2-1234"
  • Send the annotated image back to the user via the message tool with media: "file:///tmp/find-package-result.jpg"
  1. If no match is found in this photo, tell the user and ask if there are more shelves to check

Step 4: Report results

When a package is found:

  • Send the annotated photo with the red bounding box
  • Say something like: "找到了!你的快递在这里,取件码 5-2-1234"

If the user has multiple pickup codes (they mentioned several or you detected multiple in the screenshot):

  • Track which ones have been found and which are still missing
  • After each shelf photo, report: "已找到 2/3 个快递,还有 1 个没找到(取件码:7-3-5678)"

When all packages are found:

  • "全部找到了!祝取件顺利~"

When no match found after all photos:

  • "在这些照片里没有找到你的快递,要不要再拍几张其他货架的照片?"

Important Notes

  • Always communicate in Chinese — this feature is for Chinese delivery stations (驿站/快递柜)
  • Be patient — users may be unfamiliar with taking clear shelf photos. If OCR is unclear, ask them to retake with better lighting or angle
  • The pickup code format varies by delivery company. Common formats:
    • X-Y-ZZZZ (e.g., 5-2-1234)
    • Just numbers on a label
    • QR codes (if you can't read QR, tell the user to provide the text code instead)
  • When drawing bounding boxes, make them visually prominent: thick red lines, with the pickup code label above the box
  • If the shelf photo is blurry or codes are unreadable, ask for a clearer photo rather than guessing

Sending Messages

Use the message tool with channel: "telegram":

{
  "action": "send",
  "channel": "telegram",
  "message": "请发一下你的取件码~可以直接打字,也可以截图给我"
}

Send with annotated image:

{
  "action": "send",
  "channel": "telegram",
  "message": "找到了!你的快递在红框标记的位置",
  "media": "file:///tmp/find-package-result.jpg"
}
安全使用建议
This skill appears coherent and contains only a local Python annotation script plus instructions to use the platform's vision capability and message tool. Before installing, confirm: (1) your OpenClaw environment provides the message/Telegram integration used to deliver results; (2) Pillow (pip3 install Pillow) is available if you want to run annotate.py locally; and (3) users understand they will be sending photos (privacy of images). If your environment requires explicit credentials to send Telegram messages, ensure those credentials are stored and granted by the platform rather than the skill itself.
功能分析
Type: OpenClaw Skill Name: find-package Version: 1.0.0 The 'find-package' skill is designed to help users locate delivery packages by matching pickup codes to shelf photos. It uses a local Python script (scripts/annotate.py) to draw bounding boxes on images and communicates with users via Telegram. The code and instructions (SKILL.md) are consistent with the stated purpose and do not exhibit signs of data exfiltration, malicious execution, or harmful prompt injection.
能力评估
Purpose & Capability
Name/description (find-package) match the contents: the skill needs image-processing (vision + a local Python script to draw boxes). The only declared runtime requirement is python3, which is appropriate for the included annotate.py script. No unrelated binaries or credentials are requested.
Instruction Scope
SKILL.md instructs the agent to extract pickup codes from user-provided images, confirm the code with the user, run the local annotate.py to draw red bounding boxes, and send annotated images via the message tool. Instructions reference only images and pickup codes; they do not ask the agent to read unrelated files, environment variables, or external endpoints.
Install Mechanism
No install spec (instruction-only) and only a small included Python script. The README notes a Pillow dependency (expected for image annotation). There are no downloads from external URLs or archive extraction steps.
Credentials
Requires no environment variables or credentials. The skill references sending messages on Telegram via the platform's message tool, but it does not request any Telegram tokens or other secrets itself (that integration is expected to be provided by the host platform).
Persistence & Privilege
The skill is not always-enabled and does not request elevated or persistent privileges. It does not modify other skills or system-wide configuration. Autonomous invocation is allowed by default (platform behavior) but is not combined with any broad credential access.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install find-package
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /find-package 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
- Initial release of the find-package skill for Chinese delivery stations. - Helps users locate their packages on delivery shelves by matching user-provided pickup codes to shelf photos. - Supports text and screenshot input for pickup codes, with OCR applied as needed. - Guides users step-by-step in Chinese, confirming codes, requesting photos, and reporting results with annotated images. - Sends annotated shelf photos with prominent red bounding boxes marking the identified package. - Handles multiple pickup codes and provides clear feedback throughout the package-finding process.
元数据
Slug find-package
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

find-package 是什么?

Help users locate their packages on delivery shelves by matching pickup codes to shelf photos. Trigger this skill when a user mentions finding packages, pick... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 91 次。

如何安装 find-package?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install find-package」即可一键安装,无需额外配置。

find-package 是免费的吗?

是的,find-package 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

find-package 支持哪些平台?

find-package 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 find-package?

由 fjh(@noroot777)开发并维护,当前版本 v1.0.0。

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